from sentence_transformers import SentenceTransformer
model = SentenceTransformer('moka-ai/m3e-large')
# print(model)
# model.save('/Users/shaoqintian/chroma/intfloat/multilingual-e5-large/')

#Our sentences we like to encode
sentences = ['This framework generates embeddings for each input sentence',
    'Sentences are passed as a list of string.', 
    'The quick brown fox jumps over the lazy dog.']

#Sentences are encoded by calling model.encode()
sentence_embeddings = model.encode(sentences)

#Print the embeddings
for sentence, embedding in zip(sentences, sentence_embeddings):
    print("Sentence:", sentence)
    print("Embedding:", embedding)
    print("")